A compression artifact is a particular type of data error that is typically the result of quantization in lossy data compression. Traditional compression artifacts include blockiness, blur, noise, and ring. Automatic measuring of compression artifacts is described e.g. in “A Universal Image Quality Index” by Z. Wang, and A. C. Bovik, IEEE Signal Processing Letters, vol. 9, p. 81-84, March 2002, which describes a simple Structure Similarity (SSIM) indexing algorithm.
A channel artifact is the data error subject to data loss, which in most networks corresponds to packet loss. A single packet loss affects an initial set of macro-blocks (MBs). The artifacts of each single packet loss can propagate to the previous and/or the following frames as a result of inter-frame prediction of the video codec. Channel artifacts can be automatically measured as described in a co-pending patent application [2], which describes a method for estimating on bit-stream level, before error concealment, a video quality that will be obtained after the error concealment.
The perception of streamed video over lossy network is influenced by both compression artifacts and channel artifacts. ITU-T SG12/Q14P.NBAMS deals with methods for evaluating viewer perception when there are both compression artifacts and channel artifacts in video sequences.
Normally, the evaluation results are expressed as an evaluation score, which are mapped, both for compression artifacts or channel artifacts, to a score between 1 and 5 according to the definition of Mean Opinion Score (MOS). The score levels are described in Tab.1.
TABLE 1Mean Opinion Score (MOS)MOSDescription1No artifacts perceived2Recognized artifacts, but totally not influence perception3Perceived artifacts, but not annoying4Clear artifacts, a little annoying5Heavy artifacts, very annoying
Though several researchers addressed the evaluation problem of compression artifacts or channel artifacts respectively, few studies focus on the joint perception considering both compression artifacts and channel artifacts. A traditional solution is to evaluate the overall distortion by averaging compression artifacts and channel artifacts. E.g. T. Liu, Y. Wang, J. Boyce, H. Yang, and Z. Wu in “A Novel Video Quality metric for Low Bit-rate Video Considering both Coding and Packet-loss Artifacts”, Special Issue on Visual Media Quality Assessment, IEEE Journal of Selected Topics in Signal Processing, Vol. 3, No. 2, pp. 280-293, April 2009, generate the overall artifacts by a linear combination of compression artifacts and channel artifacts. The term “artifact level” is to be understood such that higher artifact level corresponds to more distortion, and vice versa. Thus, low distortion and low artifact levels are generally desired.
For accurate video quality estimation, and for a video quality control based on such estimation, both the existing average and linear combination models are not efficient enough. For example, channel artifacts seem more annoying in a video with very low compression artifacts, while it is much more acceptable in a video with high compression artifacts. This phenomenon cannot be predicted by average and linear combination models.